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A three-dimensional dataset of Inconel-625 generated as part of the Air Force Research Laboratory’s Additive Manufacturing Challenge Series is considered to interrogate modeling errors in a crystal-plasticity finite-element (CPFE) framework. Grain-average elastic strains from this framework are compared to measurements made with far-field high-energy X-ray diffraction microscopy (ff-HEDM) on a specimen loaded in tension at room temperature. The ff-HEDM measurements, taken when the specimen was held under load control, were made on the same microstructure considered in the CPFE framework. This one-to-one comparison enables a thorough investigation into modeling discrepancies, specifically those induced by improper boundary condition selection and inability to model stress relaxation events which are a likely characteristic of intermittent plasticity. It is shown that erroneously constraining the Poisson effect locally with kinematic boundary conditions induces over-estimates of off-loading-axis normal strains as far as 100 $$\upmu $$ m away from the over-constrained surface, which is roughly 14% of the overall height of the polycrystal in the loading direction. A second set of boundary conditions that relaxes the constraints on the previously over-constrained surface showed clear quantitative improvement in model predictions. Specifically, the errors in the normal components of strains in the off-loading-axes decreased. Further, it was observed that irrespective of which of the two boundary conditions was applied, the CPFE framework deviates considerably from measurements in the plastic regime compared to the elastic regime. This is mainly due to the increased frequency of strain drop (or stress relaxation) events occurring in the plastic regime, most likely caused by shearing of $$\gamma ^{\prime}$$ precipitates and other intermittent dislocation activity. The CPFE framework is unable to accommodate the stress relaxation in grains. Nevertheless, the framework is interrogated for its ability to predict such events by comparing predicted slip fields with measured grain-level relaxation events. It is demonstrated that the set of grains experiencing a strain drop (from ff-HEDM measurements) collectively had higher values of plastic strain (calculated from CPFE simulations) compared to the set of grains that did not experience a strain drop.

The Sandia Fracture Challenges provide a forum for the mechanics community to assess its ability to predict ductile fracture through a blind, round-robin format where mechanicians are challenged to predict the deformation and failure of an arbitrary geometry given experimental calibration data. The Third Challenge (SFC3) required participants to predict fracture in an additively manufactured (AM) 316L stainless steel bar containing through holes and internal cavities that could not have been conventionally machined. The volunteer participants were provided extensive data including tension and notched tensions tests of 316L specimens built on the same build-plate as the Challenge geometry, micro-CT scans of the Challenge specimens and geometric measurements of the feature based on the scans, electron backscatter diffraction (EBSD) information on grain texture, and post-test fractography of the calibration specimens. Surprisingly, the global behavior of the SFC3 geometry specimens had modest variability despite being made of AM metal, with all of the SFC3 geometry specimens failing under the same failure mode. This is attributed to the large stress concentrations from the holes overwhelming the stochastic local influence of the AM voids and surface roughness. The teams were asked to predict a number of quantities of interest in the response based on global and local measures that were compared to experimental data, based partly on Digital Image Correlation (DIC) measurements of surface displacements and strains, including predictions of variability in the resulting fracture response, as the basis for assessment of the predictive capabilities of the modeling and simulation strategies. Twenty-one teams submitted predictions obtained from a variety of methods: the finite element method (FEM) or the mesh-free, peridynamic method; solvers with explicit time integration, implicit time integration, or quasi-statics; fracture methods including element deletion, peridynamics with bond damage, XFEM, damage (stiffness degradation), and adaptive remeshing. These predictions utilized many different material models: plasticity models including J2 plasticity or Hill yield with isotropic hardening, mixed Swift-Voce hardening, kinematic hardening, or custom hardening curves; fracture criteria including GTN model, Hosford-Coulomb, triaxiality-dependent strain, critical fracture energy, damage-based model, critical void volume fraction, and Johnson-Cook model; and damage evolution models including damage accumulation and evolution, crack band model, fracture energy, displacement value threshold, incremental stress triaxiality, Cocks-Ashby void growth, and void nucleation, growth, and coalescence. Teams used various combinations of calibration data from tensile specimens, the notched tensile specimens, and literature data. A detailed comparison of results based of these different methods is presented in this paper to suggest a set of best practices for modeling ductile fracture in situations like the SFC3 AM-material problem. All blind predictions identified the nominal crack path and initiation location correctly. The SFC3 participants generally fared better in their global predictions of deformation and failure than the participants in the previous Challenges, suggesting the relative maturity of the models used and adoption of best practices from previous Challenges. This paper provides detailed analyses of the results, including discussion of the utility of the provided data, challenges of the experimental-numerical comparison, defects in the AM material, and human factors.

This paper explores the efficacy of employing local damage models, normally applied to ductile material systems manufactured by subtractive techniques, to additively manufactured laboratory specimens. While these specimens were ductile and metallic, their additive character (i.e. porosity and surface roughness) could have had potential to activate multiple life-limiting failure paths, thus obfuscating failure prediction. Herein, two damage models are considered and compared: the micromechanical Gurson–Tvergaard–Needleman model and a Crack Band model of the strain-based, phenomenological genre. Simulations used to calibrate elastic and plastic material properties and predict damage in a novel, non-standard specimen were quasi-static, explicit. Both damage models proved capable in resolving the experimentally-observed failure path and associated loading conditions. The analyses described herein were made as part of the Third Sandia Fracture Challenge.

In an effort to reproduce computationally the observed evolution of microstructurally small fatigue cracks (MSFCs), a method is presented for generating conformal, finite-element (FE), volume meshes from 3D measurements of MSFC propagation. The resulting volume meshes contain traction-free surfaces that conform to incrementally measured 3D crack shapes. Grain morphologies measured using near-field high-energy X-ray diffraction microscopy are also represented within the FE volume meshes. Proof-of-concept simulations are performed to demonstrate the utility of the mesh-generation method. The proof-of-concept simulations employ a crystal-plasticity constitutive model and are performed using the conformal FE meshes corresponding to successive crack-growth increments. Although the simulations for each crack increment are currently independent of one another, they need not be, and transfer of material-state information among successive crack-increment meshes is discussed. The mesh-generation method was developed using post-mortem measurements, yet it is general enough that it can be applied to in-situ measurements of 3D MSFC propagation.

An over-the-counter methodology to predict fracture initiation and propagation in the challenge specimen of the Second Sandia Fracture Challenge is detailed herein. This pragmatic approach mimics that of an engineer subjected to real-world time constraints and unquantified uncertainty. First, during the blind prediction phase of the challenge, flow and failure locus curves were calibrated for Ti–6Al–4V with provided tensile and shear test data for slow (0.0254 mm/s) and fast (25.4 mm/s) loading rates. Thereafter, these models were applied to a 3D finite-element mesh of the non-standardized challenge geometry with nominal dimensions to predict, among other items, crack path and specimen response. After the blind predictions were submitted to Sandia National Labs, they were improved upon by addressing anisotropic yielding, damage initiation under shear dominance, and boundary condition selection.

The study of fatigue in metals, and fatigue initiation specifically, lends itself to analysis via an emerging set of characterization and modeling tools that describe polycrystals on the meso- or microstructural length scale. These include three-dimensional characterization techniques, elastic anisotropic and visco-plastic stress models, new approaches to the statistical description of stress and strain distributions, synthetic microstructure modeling, and improved tools for manipulating the large datasets generated. A specific example of analysis in both 2D and 3D of fatigue cracks in a nickel-based superalloy is given where all the cracks are effectively coincident with coherent twin boundaries. A spectral method is used to analyze the stress state based on a fully anisotropic elastic calculation. The results indicate that, although a high resolved shear stress is associated with the locations of the observed cracks, the length of the trace of the twin boundary is more strongly correlated with crack formation.

The Park–Paulino–Roesler (PPR) potential-based model is a cohesive constitutive model formulated to be consistent under a high degree of mode-mixity. Herein, the PPR’s generalization to three-dimensions is detailed, its implementation in a finite element framework is discussed, and its use in single-core and high performance computing (HPC) applications is demonstrated. The PPR model is shown to be an effective constitutive model to account for crack nucleation and propagation in a variety of applications including adhesives, composites, linepipe steel, and microstructures.

Existing and emerging methods in computational mechanics are rarely validated against problems with an unknown outcome. For this reason, Sandia National Laboratories, in partnership with US National Science Foundation and Naval Surface Warfare Center Carderock Division, launched a computational challenge in mid-summer, 2012. Researchers and engineers were invited to predict crack initiation and propagation in a simple but novel geometry fabricated from a common off-the-shelf commercial engineering alloy. The goal of this international Sandia Fracture Challenge was to benchmark the capabilities for the prediction of deformation and damage evolution associated with ductile tearing in structural metals, including physics models, computational methods, and numerical implementations currently available in the computational fracture community. Thirteen teams participated, reporting blind predictions for the outcome of the Challenge. The simulations and experiments were performed independently and kept confidential. The methods for fracture prediction taken by the thirteen teams ranged from very simple engineering calculations to complicated multiscale simulations. The wide variation in modeling results showed a striking lack of consistency across research groups in addressing problems of ductile fracture. While some methods were more successful than others, it is clear that the problem of ductile fracture prediction continues to be challenging. Specific areas of deficiency have been identified through this effort. Also, the effort has underscored the need for additional blind prediction-based assessments.

Ductile failure of structural metals is relevant to a wide range of engineering scenarios. Computational methods are employed to anticipate the critical conditions of failure, yet they sometimes provide inaccurate and misleading predictions. Challenge scenarios, such as the one presented in the current work, provide an opportunity to assess the blind, quantitative predictive ability of simulation methods against a previously unseen failure problem. Rather than evaluate the predictions of a single simulation approach, the Sandia Fracture Challenge relies on numerous volunteer teams with expertise in computational mechanics to apply a broad range of computational methods, numerical algorithms, and constitutive models to the challenge. This exercise is intended to evaluate the state of health of technologies available for failure prediction. In the first Sandia Fracture Challenge, a wide range of issues were raised in ductile failure modeling, including a lack of consistency in failure models, the importance of shear calibration data, and difficulties in quantifying the uncertainty of prediction [see Boyce et al. (Int J Fract 186:5–68, 2014) for details of these observations]. This second Sandia Fracture Challenge investigated the ductile rupture of a Ti–6Al–4V sheet under both quasi-static and modest-rate dynamic loading (failure in ∼∼ 0.1 s). Like the previous challenge, the sheet had an unusual arrangement of notches and holes that added geometric complexity and fostered a competition between tensile- and shear-dominated failure modes. The teams were asked to predict the fracture path and quantitative far-field failure metrics such as the peak force and displacement to cause crack initiation. Fourteen teams contributed blind predictions, and the experimental outcomes were quantified in three independent test labs. Additional shortcomings were revealed in this second challenge such as inconsistency in the application of appropriate boundary conditions, need for a thermomechanical treatment of the heat generation in the dynamic loading condition, and further difficulties in model calibration based on limited real-world engineering data. As with the prior challenge, this work not only documents the ‘state-of-the-art’ in computational failure prediction of ductile tearing scenarios, but also provides a detailed dataset for non-blind assessment of alternative methods., National Science Foundation (U.S.)

A simple, nonstandardized material test specimen, which fails along one of two different likely crack paths, is considered herein. The result of deviations in geometry on the order of tenths of a millimeter, this ambiguity in crack path motivates the consideration of as-manufactured component geometry in the design, assessment, and certification of structural systems. Herein, finite element models of as-manufactured specimens are generated and subsequently analyzed to resolve the crack-path ambiguity. The consequence and benefit of such a “personalized” methodology is the prediction of a crack path for each specimen based on its as-manufactured geometry, rather than a distribution of possible specimen geometries or nominal geometry. The consideration of as-manufactured characteristics is central to the Digital Twin concept. Therefore, this work is also intended to motivate its development.

The induction of sleep would depend on interaction between gabaergic system and the pineal gland through its main hormone melatonin. Until few years ago benzodiazepines were the only drugs effective in the treatment of insomnia. Recently, however, both melatonin and acupressure have appear to be active in sleep disorders. The aim of study was to evaluate the efficacy of HT 7 point acupressure in insomnia.The study enrolled 25 patients affected by sleep disorders, 14 of whom had a neoplastic disease. They were treated by HT 7 stimulation for al least two consecutive weeks using a medical device named H7 Insomnia Control.An improvement in the quality of sleep was achieved in 15/25 (60%) patients, with a more evident efficacy in cancer patients (11/14 [79%]).This study confirms previous clinical data showing the efficacy of acupressure in the treatment of sleep disorders, particularly in cancer-related insomnia.

Alopecia still remains one of the most untreatable side-effects induced by cancer chemotherapy. According to the phytotherapeutic tradition, Panicum Miliaceum has been proven to be effective in the prevention of hair loss for different reasons. At present, however, there are no data about its possible efficacy in the treatment of cancer chemotherapy-induce alopecia. The aim of this study was to analyze the efficacy of Panicum Miliaceum in cancer patients treated with the most potent chemotherapeutic drugs in terms of hair loss, consisting of cisplatin (CDDP) and anthracyclines.This case-control study included 28 cancer patients concomitantly treated with Panicum Miliaceum and 56 patients receiving the same combinations of chemotherapy alone as a control group. Panicum Miliaceum was given orally at 300 mg (daily dose) 3 times per day, every day until the end of chemotherapy. The grade of hair loss was assessed by World Health Organization (WHO) criteria.The percentage of alopecia of third grade observed in patients concomitantly treated with Panicum Miliaceum in association with CDDP-containing regimens was significantly lower than that found in those who received the chemotherapy only. The percentage was also lower under anthracycline-containing schedules, without, however, statistically significant differences. Panicum Miliaceum therapy was substantially well tolerated in all patients.This preliminary study would suggest that the concomitant treatment with Panicum Miliaceum may be effective in preventing hair loss induced by CDDP-containing chemotherapies, whereas the benefit was lower in patients treated with anthracyclines. Future randomized studies will be necessary to confirm these preliminary

A microstructure-based capability for forecasting microcrack nucleation in the nickel-based superalloy LSHR is proposed, implemented, and partially verified. Specifically, gradient crystal plasticity is applied to finite-element models of the experimentally measured, 3D microstructure wherein a microcrack is known to have nucleated along a coherent Σ3 boundary. The framework is used to analyze this particular nucleation event and conduct an extensive grain boundary analysis study, the results of which underpin the importance that elastic anisotropy and coherency have in the localization of plastic slip.

This work focuses on the major cause of life limiting behavior in Ni-based superalloys for high pressure and temperature turbine disks applications in low cycle fatigue. Specific ideas of local microstructure features, such as the role of as large as (ALA) grains, in promoting slip localization in directly measured 3D microstructures were tested with finite element method (FEM) simulations with crystal plasticity. Synthetic microstructures with experimentally determined microstructurally small fatigue crack weakest link features of ALA grains comprise the test cases. A Rene88 damage tolerant (R88DT) dataset, from electron backscatter diffraction, was used to instantiate approximately 1.5 million elements and 200 grains from FEM sensitivity studies. Changing mesh resolution minimally impacted global damage response, but local convergence required the maximum resolution. The present results help to quantify the deleterious impact of ALA grains in Ni-based superalloys to extend service life.

Corticosteroids, antidopaminergig agents and 5-HT3 antagonists are the most commonly used drugs in the treatment of chemotherapy-induced vomiting. Acupuncture and acupressure have also appeared to exert antiemetic effects. The aim of this study was to evaluate the efficacy of acupressure in the treatment of chemotherapy-induced vomiting resistant to the standard antiemetic therapies.The study included 40 consecutive advanced cancer patients with untreatable chemotherapy-induced vomiting. Colorectal cancer, lung cancer and breast cancer were the neoplasm most frequent in our patients. According to tumour histotype, patients received chemotherapeutic regimens containing the main emetic cytotoxic agents, including cisplatin and athracyclines. Acupressure was made by PC6 point stimulation for at least 6 h/day at the onset of chemotherapy.The therapeutic approach was well accepted by the overall patients. An evident improvement in the emetic symptomatology was achieved in 28/40 (70%) patients, without significant differences in relation to neither tumor histotype, nor type of chemotherapeutic agent.This preliminary study seems to suggest that a bioenergetic approach by acupressure on PC6 point may be effective in the treatment of chemotherapy-induced vomiting resistant to the conventional pharmacological strategies, as previously demonstrated for vomiting occurring during pregnancy.